Hepatic stellate cells (HSCs) are the primary fibrogenic cells in the liver, and their activation plays a crucial role in the development and progression of hepatic fibrosis. Here, we report that retinoid X receptor-alpha (RXRα), a unique member of the nuclear receptor superfamily, is a key modulator of HSC activation and liver fibrosis. RXRα exerts its effects by modulating calcium/calmodulin-dependent protein kinase kinase β (CaMKKβ)-mediated activation of AMP-activated protein kinase-alpha (AMPKα). In addition, we demonstrate that K-80003, which binds RXRα by a unique mechanism, effectively suppresses HSC activation, proliferation, and migration, thereby inhibiting liver fibrosis in the CCl₄ and amylin liver NASH (AMLN) diet animal models. The effect is mediated by AMPKα activation, promoting mitophagy in HSCs. Mechanistically, K-80003 activates AMPKα by inducing RXRα to form condensates with CaMKKβ and AMPKα via a two-phase process. The formation of RXRα condensates is driven by its N-terminal intrinsic disorder region and requires phosphorylation by CaMKKβ. Our results reveal a crucial role of RXRα in liver fibrosis regulation through modulating mitochondrial activities in HSCs. Furthermore, they suggest that K-80003 and related RXRα modulators hold promise as therapeutic agents for fibrosis-related diseases.

Drug resistance is one of the key factors affecting the effectiveness of cancer treatment methods, including chemotherapy, radiotherapy, and immunotherapy. Its occurrence is related to factors such as mRNA expression and methylation within cancer cells. If drug resistance in patients can be accurately identified early, doctors can devise more effective treatment plans, which is of great significance for improving patients' survival rates and quality of life. Cancer drug resistance prediction based on artificial intelligence (AI) technology has emerged as a current research hotspot, demonstrating promising application prospects in guiding clinical individualized and precise medication for cancer patients. This review aims to comprehensively summarize the research progress in utilizing AI algorithms to analyze multi-omics data including genomics, transcriptomics, epigenomics, proteomics, metabolomics, radiomics, and histopathology, for predicting cancer drug resistance. It provides a detailed exposition of the processes involved in data processing and model construction, examines the current challenges faced in this field and future development directions, with the aim of better advancing the progress of precision medicine.

Acute lung injury (ALI) has been a kind of acute and severe disease that is mainly characterized by systemic uncontrolled inflammatory response to the production of huge amounts of reactive oxygen species (ROS) in the lung tissue. Given the critical role of ROS in ALI, a Fe₃O₄ loaded bovine serum albumin (BSA) nanocluster (BF) was developed to act as a nanomedicine for the treatment of ALI. Combining with NIR irradiation, it exhibited excellent ROS scavenging capacity. Significantly, it also displayed the excellent antioxidant and anti-inflammatory functions for lipopolysaccharides (LPS) induced macrophages (RAW264.7), and Sprague Dawley rats via lowering intracellular ROS levels, reducing inflammatory factors expression levels, inducing macrophage M2 polarization, inhibiting NF-κB signaling pathway, increasing CD4⁺/CD8⁺ T cell ratios, as well as upregulating HSP70 and CD31 expression levels to reprogram redox homeostasis, reduce systemic inflammation, activate immunoregulation, and accelerate lung tissue repair, finally achieving the synergistic enhancement of ALI immunotherapy. It finally provides an effective therapeutic strategy of BF + NIR for the management of inflammation related diseases.

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In managing metabolic dysfunction-associated steatotic liver disease, which affects over 30% of the general population, effective noninvasive biomarkers for assessing disease severity, monitoring disease progression, predicting the development of liver-related complications, and assessing treatment response are crucial. The advantage of simple fibrosis scores lies in their widespread accessibility through routinely performed blood tests and extensive validation in different clinical settings. They have shown reasonable accuracy in diagnosing advanced fibrosis and good performance in excluding the majority of patients with a low risk of liver-related complications. Among patients with elevated serum fibrosis scores, a more specific fibrosis and imaging biomarker has proved useful to accurately identify patients at risk of liver-related complications. Among specific fibrosis blood biomarkers, enhanced liver fibrosis is the most widely utilized and has been approved in the United States as a prognostic biomarker. For imaging biomarkers, the availability of vibration-controlled transient elastography has been largely improved over the past years, enabling the use of liver stiffness measurement (LSM) for accurate assessment of significant and advanced fibrosis, and cirrhosis. Combining LSM with other routinely available blood tests enhances the ability to diagnose at-risk metabolic dysfunction-associated steatohepatitis and predict liver-related complications, some reaching an accuracy comparable to that of liver biopsy. Magnetic resonance imaging-based modalities provide the most accurate quantification of liver fibrosis, though the current utilization is limited to research settings. Expanding their future use in clinical practice depends on factors such as cost and facility availability.

Medication reconciliation plays a key role in improving patient medication safety,reducing inappropriate polypharmacy,and promoting the high-quality development of pharmaceutical services.Compared to advanced international guidelines,China's medication reconciliation service standards have deficiencies in areas such as definition and process design,and multidisciplinary team building.There is a need to establish a comprehensive medication reconciliation effect evaluation index system,develop pharmacist-led multidisciplinary teams,promote the advancement of artificial intelligence and big data technologies,and strengthen outpatient and community medication reconciliation coverage,thereby contributing to the high-quality development of pharmaceutical services in China.

The International System for Human Cytogenomic Nomenclature (ISCN) is a standardized international nomenclature system established by the International Standing Committee on Human Cytogenomic Nomenclature (ISCN SC). It is designed for describing chromosomal or genomic abnormalities detected by commonly used genetic and genomic techniques including but not limited to karyotyping, fluorescence in situ hybridization, microarray, genome mapping, various region-specific assays, and high-throughput sequencing. With a history spanning over six decades, the ISCN was revised by the ISCN SC in 2024 and officially published in September 2024. This article provides a summary for the updates introduced in the 2024 edition of the International System for Human Cytogenomic Nomenclature.

Objective:This study evaluates the horizontal sound localization ability of young and middle-aged individuals with symmetric sensorineural hearing loss (SNHL) in noisy environments. It also examines the impact of hearing loss severity and signal-to-noise ratio (SNR) on localization accuracy.Methods:In this cross-sectional study, conducted from April 2023 to April 2024, 135 young and middle-aged patients (73 males and 62 females, aged 18-60 years) with SNHL who sought care at Beijing Chaoyang Hospital, were categorized into mild, moderate, and moderate-to-severe hearing loss groups (45 per group), with 45 normal-hearing controls (23 males and 22 females, aged 20-60 years). Participants completed localization tasks in quiet and noisy environments with SNR levels of 5 dB, 0 dB, -5 dB, and-10 dB. Root mean square error (RMSE) was used to measure localization accuracy. Repeated measures ANOVA assessed the effects of hearing loss and SNR on RMSE, while, Pearson correlation evaluated the relationship between binaural 4-frequency pure-tone average (4fPTA) and RMSE. Multiple linear regression analyzed the predictive role of 4fPTA and age.Results:(1) Two-way repeated measures ANOVA showed that both hearing loss severity and SNR significantly affected RMSE ( F=92.67, P<0.01; F=430.29, P<0.01), with a significant interaction between the two factors( F=92.67, P<0.01). (2) RMSE increased with hearing loss severity. At SNRs of 5 dB, 0 dB, and-5 dB, the moderate-to-severe group had significantly higher RMSE than the mild and moderate groups ( P<0.01). No significant differences were found between mild and moderate groups ( P=0.53, 0.57, 0.22). At-10 dB SNR, significant differences were observed across all groups ( P<0.01). (3) RMSE increased non-linearly as SNR decreased. Mean RMSE values under quiet conditions and at SNRs of 5 dB, 0 dB, -5 dB, and-10 dB were (7.43±5.01)°, (9.80±5.74)°, (11.60±6.22)°, (14.56±7.07)°, and (18.74±8.02)°, respectively. (4) RMSE was significantly positively correlated with binaural 4fPTA ( r=0.54-0.58, P<0.01). Multiple linear regression analysis indicated that the binaural average 4fPTA significantly predicted RMSE ( P<0.01), explaining 30.5%-34.1% of RMSE variance. Age did not significantly contribute to RMSE variation. Conclusions:The degree of hearing loss and background noise SNR significantly affect horizontal sound localization in young and middle-aged SNHL patients. RMSE increases with hearing loss severity and decreases with higher SNR. The interaction between hearing loss and SNR is significant, and RMSE correlates with binaural 4fPTA. However, the regression model based on 4fPTA and age explains only part of the RMSE variance, suggesting other contributing factors.

The International System for Human Cytogenomic Nomenclature (ISCN) is a standardized international nomenclature system established by the International Standing Committee on Human Cytogenomic Nomenclature (ISCN SC). It is designed for describing chromosomal or genomic abnormalities detected by commonly used genetic and genomic techniques including but not limited to karyotyping, fluorescence in situ hybridization, microarray, genome mapping, various region-specific assays, and high-throughput sequencing. With a history spanning over six decades, the ISCN was revised by the ISCN SC in 2024 and officially published in September 2024. This article provides a summary for the updates introduced in the 2024 edition of the International System for Human Cytogenomic Nomenclature.
Humans ; Terminology as Topic ; Genomics ; Genome, Human/genetics*

In managing metabolic dysfunction-associated steatotic liver disease, which affects over 30% of the general population, effective noninvasive biomarkers for assessing disease severity, monitoring disease progression, predicting the development of liver-related complications, and assessing treatment response are crucial. The advantage of simple fibrosis scores lies in their widespread accessibility through routinely performed blood tests and extensive validation in different clinical settings. They have shown reasonable accuracy in diagnosing advanced fibrosis and good performance in excluding the majority of patients with a low risk of liver-related complications. Among patients with elevated serum fibrosis scores, a more specific fibrosis and imaging biomarker has proved useful to accurately identify patients at risk of liver-related complications. Among specific fibrosis blood biomarkers, enhanced liver fibrosis is the most widely utilized and has been approved in the United States as a prognostic biomarker. For imaging biomarkers, the availability of vibration-controlled transient elastography has been largely improved over the past years, enabling the use of liver stiffness measurement (LSM) for accurate assessment of significant and advanced fibrosis, and cirrhosis. Combining LSM with other routinely available blood tests enhances the ability to diagnose at-risk metabolic dysfunction-associated steatohepatitis and predict liver-related complications, some reaching an accuracy comparable to that of liver biopsy. Magnetic resonance imaging-based modalities provide the most accurate quantification of liver fibrosis, though the current utilization is limited to research settings. Expanding their future use in clinical practice depends on factors such as cost and facility availability.